The Correlation Between Providing Complementary Food and Breast-Feeding with the Growth and Development of Children Under the Age of Five Years Old (6-24 Months)

A toddler is a group on the stage of human development that is vulnerable to the risk affecting their health specifically about their growth and development. Providing the appropriate nutrition to toddlers during this risky age of 6 to 24 months is crucial in promoting a proper growth and development. The proper nourishment for toddlers at the age of 6 to 24 months includes breast-feeding and complimentary solid foods. The objective of this study was to determine the correlation between the specific characteristics of a family or a household and the provision of complementary feeding about the growth and development of children (6-24 months) in the village of Curug Cimanggis, Depok. This study used a descriptive correlational, cross-sectional approach using a sample that consisted of 102 children aged 6-24 months, which were collected using a proportional cluster sampling. Based on the Chi Square test, the researchers found no correlation between the provision of complementary feeding with a child’s growth and development. This is because breast-feeding as the source of nourishment is still the major factor that directly influences the growth and development of any toddler between the age of 6-24 months. However, by applying better financial management in conjunction with the ability to modify the practices of how families feed their toddlers, a family may raise and nurture their toddlers so they may grow according to the proper stages of development. The results of this study are expected to serve as an input in improving toddlers’ health care concerning their growth and development by promoting the importance of providing the appropriate complimentary food by the proper guidelines while continuing to breast feed toddlers between the age of 6 to 24 months

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). What are the neuronal mechanisms responsible for these changes and how does targeted stimulation by a BBCI shape population-level synaptic connectivity? The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites are strengthened for spike-stimulus delays consistent with experimentally derived spike time dependent plasticity (STDP) rules. However, the relationship between STDP mechanisms at the level of networks, and their modification with neural implants remains poorly understood. Using our model, we successfully reproduces key experimental results and use analytical derivations, along with novel experimental data. We then derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered stimulation in different regimes of cortical activity.Comment: 35 pages, 9 figure

Ambiguous correlation

Many decisions are made in environments where outcomes are determined by the realization of multiple random events. A decision maker may be uncertain how these events are related. We identify and experimentally substantiate behavior that intuitively reflects a lack of confidence in their joint distribution. Our findings suggest a dimension of ambiguity which is different from that in the classical distinction between risk and "Knightian uncertainty"

Correlation femtoscopy

The basics of correlation femtoscopy, recent results from femtoscopy in relativistic heavy ion collisions and their consequences are shortly reviewed.Comment: 10 pages, plenary review talk at Quark Matter 2005, 2 references adde

Ridge And Transverse Correlation Without Long-Range Longitudinal Correlation

A simple phenomenological relationship between the ridge distribution in Delta eta and the single-particle distribution in eta can be established from the PHOBOS data on both distributions. The implication points to the possibility that it is not necessary to have long-range longitudinal correlation to explain the data. An interpretation of the relationship is then developed, based on the recognition that longitudinal uncertainty of the initial configuration allows for non-Hubble-like expansion at early time. It is shown that the main features of the ridge structure can be explained in a model where transverse correlation stimulated by semihard partons is the principal mechanism. This work is related to the azimuthal anisotropy generated by minijets in Au-Au collisions at 0.2 TeV on the one hand and to the ridge structure seen in pp collisions at 7 TeV on the other hand.Physic

Optical Correlation

Pattern recognition may supplement or replace certain navigational aids on spacecraft in docking or landing activities. The need to correctly identify terrain features remains critical in preparation of autonomous planetary landing. One technique that may solve this problem is optical correlation. Correlation has been successfully demonstrated under ideal conditions; however, noise significantly affects the ability of the correlator to accurately identify input signals. Optical correlation in the presence of noise must be successfully demonstrated before this technology can be incorporated into system design. An optical correlator is designed and constructed using a modified 2f configuration. Liquid crystal televisions (LCTV) are used as the spatial light modulators (SLM) for both the input and filter devices. The filter LCTV is characterized and an operating curve is developed. Determination of this operating curve is critical for reduction of input noise. Correlation of live input with a programmable filter is demonstrated

Correlation plenoptic imaging

Plenoptic imaging is a promising optical modality that simultaneously captures the location and the propagation direction of light in order to enable three-dimensional imaging in a single shot. However, in classical imaging systems, the maximum spatial and angular resolutions are fundamentally linked; thereby, the maximum achievable depth of field is inversely proportional to the spatial resolution. We propose to take advantage of the second-order correlation properties of light to overcome this fundamental limitation. In this paper, we demonstrate that the momentum/position correlation of chaotic light leads to the enhanced refocusing power of correlation plenoptic imaging with respect to standard plenoptic imaging.Comment: 6 pages, 3 figure

Endogenous Correlation

We model endogenous correlation in asset returns via the role of heterogeneous expectations in investor types, and the dynamic impact of imitative learning by investors. Learning is driven by relative performance. In addition, we allow a cautious slow learning pace to reflect institutional conditions. Imitative learning shapes the market ecology that influences price formation. Using the model of non-imitative agents as a benchmark, our results show that the dynamics of imitative learning endogenously induce a significant degree of asset dependency and patterns of non-constant correlation. The asymmetric learning effect on correlation, however, implies a self-reinforcing process, where a bearish condition amplifies the effect that further exacerbates asset dependency. We conclude that imitative learning, even when rational, can to a certain extent account for the phenomena of market crashes. Our results have implications for transparency in regulation issues

Correlation-induced localization

A new paradigm of Anderson localization caused by correlations in the long-range hopping along with uncorrelated on-site disorder is considered which requires a more precise formulation of the basic localization-delocalization principles. A new class of random Hamiltonians with translation-invariant hopping integrals is suggested and the localization properties of such models are established both in the coordinate and in the momentum spaces alongside with the corresponding level statistics. Duality of translation-invariant models in the momentum and coordinate space is uncovered and exploited to find a full localization-delocalization phase diagram for such models. The crucial role of the spectral properties of hopping matrix is established and a new matrix inversion trick is suggested to generate a one-parameter family of equivalent localization/delocalization problems. Optimization over the free parameter in such a transformation together with the localization/delocalization principles allows to establish exact bounds for the localized and ergodic states in long-range hopping models. When applied to the random matrix models with deterministic power-law hopping this transformation allows to confirm localization of states at all values of the exponent in power-law hopping and to prove analytically the symmetry of the exponent in the power-law localized wave functions.Comment: 14 pages, 8 figures + 5 pages, 2 figures in appendice